Verizon Uses Advanced Analytics to Rationalize Its Tail Spend Suppliers

Abstract

The Verizon Global Supply Chain organization currently manages thousands of active supplier contracts. These contracts account for several billion dollars of annualized Verizon spend. Managing thousands of suppliers, controlling spend, and achieving the best price per unit (PPU) through negotiations are costly and labor-intensive tasks handled by Verizon strategic sourcing teams. Verizon engages thousands of suppliers for many reasons—best price, diversity, short-term requirements, and so forth. Whereas managing a few larger spend suppliers can be done manually by dedicated sourcing managers, managing thousands of smaller suppliers at the tail spend is challenging, can often introduce risk, and can be expensive. At Verizon, a unique blend of descriptive, predictive, and prescriptive analytics, as well as Verizon-specific sourcing acumen was leveraged to tackle this problem and rationalize Verizon’s tail spend suppliers. Through the creative application of operations research, machine learning, text mining, natural language processing, and artificial intelligence, Verizon reduced spend by millions of dollars and acquired the lowest PPU for the sourced products and services. Other benefits Verizon realized were centralized and transparent contract and supplier relationship management, overhead cost reduction, decreased contract execution lead time, and service quality improvement for Verizon’s strategic sourcing teams.